Evaluation of diagnostic criteria of DSM-IV-TR for diagnosis of internet addiction disorder

authors:

avatar S. Salman Alavi 1 , * , avatar Fereshteh Jannatifard 2 , avatar Mehdi Eslami 3 , avatar Hossein Rezapour 4

Msc of Psychology, School of Management and Medical Informatics, Isfahan University of Medical Sciences and Health Services, Isfahan, Iran.
MS of Health, Education Organization of Isfahan.Gay religion, Isfahan, Iran.
Psychiatrist, Shohadaye Lenjan Hospital, Zarinshahr, Iran
Msc of Psychometry, Islamic Azad University, Naeen Branch, Naeen, Iran.

How To Cite Alavi S S, Jannatifard F, Eslami M, Rezapour H. Evaluation of diagnostic criteria of DSM-IV-TR for diagnosis of internet addiction disorder. Zahedan J Res Med Sci. 2011;13(6):e93833. 

Abstract

Background: The latest version of Diagnostic and Statistical Manual for Mental Disorder (DSM-IV-TR), classified internet addiction disorder under "impulse control disorder not elsewhere classified". This study evaluates diagnostic criteria of DSM-IV-TR for diagnosis of IAD correspondence with Iranian society and culture.
 
 
Materials and Method: This is a descriptive-analytical and cross-sectional research. For these purpose 400 students of Isfahan universities were entered into the study. Sampling method was quota sampling. At first we performed clinical interview (based on DSM-IV-TR) for all cases, then the interviews reevaluated by another specialist. Data analysis has been done by content validity, inter-scorer reliability (Kappa coefficient) and test-retest with SPSS1-14 software.
 
 
Results: Content validity of diagnostic interviews match with DSM-IV-TR criteria and their content is appropriate, two items including "chatroom pathological use" and "monthly fees for internet" were added to promote its validity.  Internal reliability (Kappa) was 0.80 and test –retest reliability was r=0.74(p<0.01).
 
 
Conclusion: Results suggest that diagnostic criteria of DSM-IV-TR are valid and reliable for internet addiction diagnosis and with this clinical interview. We have a more effective way to diagnose internet addiction in the future studies

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